 Pattern recognition and subjective belief learning in a repeated constant-sum gameGames and Economic Behavior, 2012, vol. 75, issue 2, 921-935 Abstract: This paper aspires to fill a conspicuous gap in the literature regarding learning in games—the absence of empirical verification of learning rules involving pattern recognition. Weighted fictitious play is extended to detect two-period patterns in opponentsʼ behavior and to comply with the cognitive laws of subjective perception. An analysis of the data from Nyarko and Schotter (2002) uncovers significant evidence of pattern recognition in elicited beliefs and action choices. The probability that subjects employ pattern recognition depends positively on a measure of the exploitable two-period patterns in an opponentʼs action choices, in stark contrast to the minimax hypothesis. A significant proportion of the subjectsʼ competence in pattern recognition is the result of a subconscious/automatic cognitive mechanism, implying that elicited beliefs may not adequately represent the complete learning process of game players. Additionally, standard weighted fictitious play models are found to bias memory parameter estimates upwards due to mis-specification. Keywords: Behavioral game theory; Learning; Fictitious play beliefs; Pattern detection; Repeated constant-sum games (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:gamebe:v:75:y:2012:i:2:p:921-935 DOI: 10.1016/j.geb.2012.01.005 Access Statistics for this article Games and Economic Behavior is currently edited by E. Kalai More articles in Games and Economic Behavior from Elsevier |
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